Overview

Data Structures
Divisions Metrics Values
size observations 70
size variables 9
size values 630
size memory size (KB) 0
duplicated duplicate observation 0
missing complete observation 70
missing missing observation 0
missing missing variables 0
missing missing values 0
Data Types
Divisions Metrics Values
data type numerics 2
data type integers 4
data type factors/ordered 0
data type characters 3
data type Dates 0
data type POSIXcts 0
data type others 0
Job Informations
Divisions Metrics Values
dataset dataset base
dataset dataset type tbl_df
dataset target W
job samples 70 / 70 (100%)
job created 2023-11-23 22:28:52.213793
job created by dlookr






Univariate Analysis

Descriptive Statistics

Descriptive statistics and visualization of individual variables
Variables
Missing (%)
Distincts (Ratio)
Zeros
Negatives
Outliers
Tm
character
0
(0)
5
(0.071)
-
-
-
W
integer
0
(0)
47
(0.671)
0
0
0
L
integer
0
(0)
47
(0.671)
0
0
0
W-L%
numeric
0
(0)
55
(0.786)
0
0
0
GB
character
0
(0)
39
(0.557)
-
-
-
RS
integer
0
(0)
69
(0.986)
0
0
0
RA
integer
0
(0)
68
(0.971)
0
0
0
pythW-L%
numeric
0
(0)
61
(0.871)
0
0
0
Date
character
0
(0)
14
(0.2)
-
-
-


Normality Test

Normality test results of numeric variables
Variables
Mean
Min
Q1
Median
Q3
Max
Balance
W
52.49
7
29
54
73.75
104
Balanced
L
49.39
7
29
48.5
71
107
Balanced
W-L%
0.51
0.304
0.43825
0.5205
0.59725
0.682
Balanced
RS
457.67
80
253.25
467
649
947
Balanced
RA
449.99
65
268.75
450.5
647.5
855
Balanced
pythW-L%
0.5
0.332
0.43125
0.4935
0.5735
0.679
Balanced


Bivariate Analysis

Compare Numerical Variables

Relationship between two numerical variables
First Variable
Second Variable
Correlation Coefficient
W
L
0.67807
W
W-L%
0.38646
W
RS
0.97590
W
RA
0.82041
W
pythW-L%
0.36927
L
W-L%
-0.32274
L
RS
0.77335
L
RA
0.96170
L
pythW-L%
-0.30497
W-L%
RS
0.24427
1–10 of 15 rows


Compare Categorical Variables

The number of categorical variables is less than 2.


Multivariate Analysis

Correlation Analysis

Correlation Matrix

Correlation coefficient matrix of numeric variables
Second Variable
First Variable
W
L
W-L%
RS
RA
pythW-L%
W
0.678
0.386
0.976
0.820
0.369
L
0.678
-0.323
0.773
0.962
-0.305
W-L%
0.386
-0.323
0.244
-0.125
0.914
RS
0.976
0.773
0.244
0.900
0.258
RA
0.820
0.962
-0.125
0.900
-0.135
pythW-L%
0.369
-0.305
0.914
0.258
-0.135


Correlation Plot

Correlation coefficient matrix plot


Target based Analysis

Target Variable and Numeric Variables

Relationship between two numerical variables by level of target variable
Variable
Target Variable
L
W
Visuzlization of relation
Statistics
Values
Residual standard error
20.6161224
Degrees of freedom
68
Multiple R-squared
0.4597767
Adjusted R-squared
0.4518323
F-statistic
57.8738863
p-value
0

Estimate
Std. Error
t value
Pr(>|t|)
(Intercept)
16.3227878
5.3542928
3.0485423
0.0032744
L
0.7322548
0.0962545
7.6074888
0.0000000

W-L%
W
RS
W
Visuzlization of relation
Statistics
Values
Residual standard error
6.1213435
Degrees of freedom
68
Multiple R-squared
0.952373
Adjusted R-squared
0.9516726
F-statistic
1359.7629376
p-value
0

Estimate
Std. Error
t value
Pr(>|t|)
(Intercept)
-0.3707923
1.6093254
-0.2304023
0.8184709
RS
0.1154901
0.0031319
36.8749636
0.0000000

RA
W
pythW-L%
W


Target Variable and Categorical Variables

There are no categorical variables except for the target variable.



 

Created by dlookr package